## Loading required package: ggplot2
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##   [.quosures     rlang
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##   print.quosures rlang
## Loading required package: scales
## Loading required package: maptools
## Loading required package: sp
## Checking rgeos availability: TRUE
## Loading required package: maps
## Loading required package: grid
## Loading required package: Group4
## Loading required package: mapproj
## Loading required package: dplyr
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
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##     intersect, setdiff, setequal, union
## Loading required package: leaflet

Feodo

En este Markdown se intenta representar el número de botnets activas. El dataset utilizado se actualiza cada 5 minutos.

La fuente de los datos utilizados es accesible desde el siguiente enlace https://feodotracker.abuse.ch/.

Including Map

Mapa con la ubicación de las botnets.

## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
## Registered S3 methods overwritten by 'ggplot2':
##   method         from 
##   [.quosures     rlang
##   c.quosures     rlang
##   print.quosures rlang
## Loading required package: car
## Loading required package: carData
## 
## Attaching package: 'car'
## The following object is masked from 'package:dplyr':
## 
##     recode
## Loading required package: sandwich
## [1] "[*] Initial setup"
## [1] "[*] Read data from source"
##  chr "data.frame"
## Type of dataset :  
## Dimension(row x column) :  348 9 
## Current lenght:  9 & Object size: 57008 
## List of 9
##  $ DetectedDate   : chr [1:2] "POSIXct" "POSIXt"
##  $ DstIP          : chr "character"
##  $ DstPort        : chr "integer"
##  $ LastOnlineDate : chr [1:2] "POSIXct" "POSIXt"
##  $ Malware        : chr "character"
##  $ DetectedWeekday: chr "factor"
##  $ continent_name : chr "character"
##  $ country_code   : chr "character"
##  $ country_name   : chr "character"
## Types of dataset fields: Printing
##  
##  print done 
## Now let's see the values of all non-repeated fields
## 'data.frame':    348 obs. of  9 variables:
##  $ DetectedDate   : POSIXct, format: "2019-05-30 08:28:38" "2019-05-30 08:16:35" ...
##  $ DstIP          : chr  "185.244.149.206" "94.23.174.183" "185.61.149.38" "176.223.133.178" ...
##  $ DstPort        : int  447 447 447 447 443 447 447 447 443 447 ...
##  $ LastOnlineDate : POSIXct, format: "2019-06-01" "2019-06-02" ...
##  $ Malware        : chr  "TrickBot" "TrickBot" "TrickBot" "TrickBot" ...
##  $ DetectedWeekday: Factor w/ 7 levels "domingo","jueves",..: 2 2 2 2 2 2 5 5 5 5 ...
##  $ continent_name : chr  NA "Europe" "Europe" "Europe" ...
##  $ country_code   : chr  NA "CZ" "LV" "RO" ...
##  $ country_name   : chr  NA "Czech Republic" "Latvia" "Romania" ...
## Structure of the dataset fields: 
## [1] "[*] Read RAW data from MaxMind"
## [1] "[*] Subseting scans data set"
## [1] "[*] Expanding MaxMind network ranges"
## [1] "[*] Foreach IP (source and destination) identify network range using parallel computing"
## [1] "[*] Joining source IP's with geolocation data"
## [1] "[*] Tidy data and save it"

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.